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Genetic Algorithm based PID Tuning Software Design and Implementation for a DC Motor Control System

Year 2023, , 286 - 300, 29.09.2023
https://doi.org/10.54287/gujsa.1342905

Abstract

This study presents the software and implementation for proportional-integral-derivative (PID) tuning of a DC motor control system using genetic algorithm (GA). The PID parameters for a specific control structure are optimized using GA in the proposed tuning procedure. Also, integral time absolute error (ITAE) is used as a fitness function to optimize the parameters. The robustness of the control system is compared with conventional mathematical method. Simulations are carried out in MATLAB/Simulink to compare the results of a DC motor control system. Simulation results show that in terms of overshoot, steady-state error, and settling time, GA-based PID tuning approach performed better than conventional method. Additionally, a sensitivity analysis is performed to evaluate how robust the proposed approach is to parameter variations. The analysis shows that compared to the conventional method, the GA-based PID tuning algorithm is more adaptable to variations in system parameters.

References

  • Alruim Alhasan, H., & Güneş, M. (2017). A New Adaptive Particle Swarm Optimization Based on Self-Tuning of PID Controller for DC Motor System. Çukurova University Journal of the Faculty of Engineering and Architecture, 32(3), 243-249.
  • Aranza, M. F., Kustija, J., Trisno, B., & Hakim, D. L. (2016). Tunning PID controller using particle swarm optimization algorithm on automatic voltage regulator system. IOP Conference Series: Materials Science and Engineering, 128, 012038. doi:10.1088/1757-899X/128/1/012038
  • Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818-827. doi:10.1007/s40435-020-00665-4
  • Fang, H., Zhou, J., Wang, Z., Qiu, Z., Sun, Y., Lin, Y., Chen, K., Zhou, X., & Pan, M. (2022). Hybrid method integrating machine learning and particle swarm optimization for smart chemical process operations. Frontiers of Chemical Science and Engineering, 16(2), 274-287. doi:10.1007/s11705-021-2043-0
  • de Figueiredo, R., Toso, B., & Schmith, J. (2023). Auto-Tuning PID Controller Based on Genetic Algorithm. In: M. Shamsuzzoha & G. L. Raja (Eds.), Disturbance Rejection Control. IntechOpen. doi:10.5772/INTECHOPEN.110143
  • Flores-Morán, E., Yánez-Pazmiño, W., Espín-Pazmiño, L., Carrera-Manosalvas, I., & Barzola-Monteses, J. (2020, October 13-16). Particle Swarm Optimization and Genetic Algorithm PID for DC motor position controllers. In: Proceedings of the 2020 IEEE ANDESCON, Quito, Ecuador. doi:10.1109/ANDESCON50619.2020.9272127
  • Galotto, L., Pinto, J. O. P., Bottura Filho, J. A., & Lambert-Torres, G. (2007, November 5-8). Recursive least square and genetic algorithm based tool for PID controllers tuning. In: Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan. doi:10.1109/ISAP.2007.4441623
  • Ibrahim, O., Yahaya, N. Z. B., & Saad, N. (2016). PID Controller Response to Set-Point Change in DC-DC Converter Control. International Journal of Power Electronics and Drive Systems (IJPEDS), 7(2), 294-302. doi:10.11591/IJPEDS.V7.I2.PP294-302
  • Islam, Md. T., Karim, S. M. R., Sutradhar, A., & Miah, S. (2020). Fuzzy Logic and PID Controllers for DC Motor Using Genetic Algorithm. International Journal of Control Science and Engineering, 10(2), 37-41. doi:10.5923/J.CONTROL.20201002.03
  • Jayachitra, A., & Vinodha, R. (2014). Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor. Advances in Artificial Intelligence, 2014, 791230. doi:10.1155/2014/791230
  • Korkmaz, M., Aydoǧdu, Ö., & Doǧan, H. (2012, July 2-4). Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller. In: Proceedings of the 2012 International Symposium on Innovations in Intelligent Systems and Applications (INISTA), Trabzon, Türkiye. doi:10.1109/INISTA.2012.6246935
  • Taşören, A. E. (2021). Design and Realization of Online Auto Tuning PID Controller Based on Cohen-Coon Method. European Journal of Science and Technology, 24 (Special Issue), 235-239. doi:10.31590/ejosat.897727
  • Malhotra, R., Singh, N., & Singh, Y. (2011). Genetic Algorithms: Concepts, Design for Optimization of Process Controllers. Computer and Information Science, 4(2), 39-54. doi:10.5539/CIS.V4N2P39
  • Martinez-Soltero, E. G., & Hernandez-Barragan, J. (2018). Robot Navigation Based on Differential Evolution. IFAC-PapersOnLine, 51(13), 350-354. doi:10.1016/J.IFACOL.2018.07.303
  • Meena, D. C., & Devanshu, A. (2017, January 19-20). Genetic algorithm tuned PID controller for process control. In: Proceedings of the 2017 International Conference on Inventive Systems and Control (ICISC), Coimbatore, India. doi:10.1109/ICISC.2017.8068639
  • Patel, V. V. (2020). Ziegler-Nichols Tuning Method: Understanding the PID Controller. Resonance, 25(10), 1385-1397. doi:10.1007/s12045-020-1058-z
  • Pereira, D. S., & Pinto, J. O. P. (2005, July 24-28). Genetic Algorithm based system identification and PID tuning for optimum adaptive control. In: Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, CA, USA, (pp. 801-806). doi:10.1109/AIM.2005.1511081
  • Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal, 4(3), 409-421. doi:10.1016/J.ASEJ.2012.10.010
  • Saad, M. S., Jamaluddin, H., & Darus, I. Z. M. (2012). Implementation of PID controller tuning using differential evolution and genetic algorithms. International Journal of Innovative Computing Information and Control, 8(11), 7761-7779.
  • Tiwari, S., Bhatt, A., Unni, A. C., Singh, J. G., & Ongsakul, W. (2018, October 24-26). Control of DC Motor Using Genetic Algorithm Based PID Controller. In: Proceedings of the 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), Phuket, Thailand. doi:10.23919/ICUE-GESD.2018.8635662
  • Wati, D. A. R., & Hidayat, R. (2013, November 25-27). Genetic algorithm-based PID parameters optimization for air heater temperature control. In: Proceedings of the 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems (ROBIONETICS), Jogjakarta, Indonesia, (pp. 30-34). doi:10.1109/ROBIONETICS.2013.6743573
Year 2023, , 286 - 300, 29.09.2023
https://doi.org/10.54287/gujsa.1342905

Abstract

References

  • Alruim Alhasan, H., & Güneş, M. (2017). A New Adaptive Particle Swarm Optimization Based on Self-Tuning of PID Controller for DC Motor System. Çukurova University Journal of the Faculty of Engineering and Architecture, 32(3), 243-249.
  • Aranza, M. F., Kustija, J., Trisno, B., & Hakim, D. L. (2016). Tunning PID controller using particle swarm optimization algorithm on automatic voltage regulator system. IOP Conference Series: Materials Science and Engineering, 128, 012038. doi:10.1088/1757-899X/128/1/012038
  • Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818-827. doi:10.1007/s40435-020-00665-4
  • Fang, H., Zhou, J., Wang, Z., Qiu, Z., Sun, Y., Lin, Y., Chen, K., Zhou, X., & Pan, M. (2022). Hybrid method integrating machine learning and particle swarm optimization for smart chemical process operations. Frontiers of Chemical Science and Engineering, 16(2), 274-287. doi:10.1007/s11705-021-2043-0
  • de Figueiredo, R., Toso, B., & Schmith, J. (2023). Auto-Tuning PID Controller Based on Genetic Algorithm. In: M. Shamsuzzoha & G. L. Raja (Eds.), Disturbance Rejection Control. IntechOpen. doi:10.5772/INTECHOPEN.110143
  • Flores-Morán, E., Yánez-Pazmiño, W., Espín-Pazmiño, L., Carrera-Manosalvas, I., & Barzola-Monteses, J. (2020, October 13-16). Particle Swarm Optimization and Genetic Algorithm PID for DC motor position controllers. In: Proceedings of the 2020 IEEE ANDESCON, Quito, Ecuador. doi:10.1109/ANDESCON50619.2020.9272127
  • Galotto, L., Pinto, J. O. P., Bottura Filho, J. A., & Lambert-Torres, G. (2007, November 5-8). Recursive least square and genetic algorithm based tool for PID controllers tuning. In: Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan. doi:10.1109/ISAP.2007.4441623
  • Ibrahim, O., Yahaya, N. Z. B., & Saad, N. (2016). PID Controller Response to Set-Point Change in DC-DC Converter Control. International Journal of Power Electronics and Drive Systems (IJPEDS), 7(2), 294-302. doi:10.11591/IJPEDS.V7.I2.PP294-302
  • Islam, Md. T., Karim, S. M. R., Sutradhar, A., & Miah, S. (2020). Fuzzy Logic and PID Controllers for DC Motor Using Genetic Algorithm. International Journal of Control Science and Engineering, 10(2), 37-41. doi:10.5923/J.CONTROL.20201002.03
  • Jayachitra, A., & Vinodha, R. (2014). Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor. Advances in Artificial Intelligence, 2014, 791230. doi:10.1155/2014/791230
  • Korkmaz, M., Aydoǧdu, Ö., & Doǧan, H. (2012, July 2-4). Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller. In: Proceedings of the 2012 International Symposium on Innovations in Intelligent Systems and Applications (INISTA), Trabzon, Türkiye. doi:10.1109/INISTA.2012.6246935
  • Taşören, A. E. (2021). Design and Realization of Online Auto Tuning PID Controller Based on Cohen-Coon Method. European Journal of Science and Technology, 24 (Special Issue), 235-239. doi:10.31590/ejosat.897727
  • Malhotra, R., Singh, N., & Singh, Y. (2011). Genetic Algorithms: Concepts, Design for Optimization of Process Controllers. Computer and Information Science, 4(2), 39-54. doi:10.5539/CIS.V4N2P39
  • Martinez-Soltero, E. G., & Hernandez-Barragan, J. (2018). Robot Navigation Based on Differential Evolution. IFAC-PapersOnLine, 51(13), 350-354. doi:10.1016/J.IFACOL.2018.07.303
  • Meena, D. C., & Devanshu, A. (2017, January 19-20). Genetic algorithm tuned PID controller for process control. In: Proceedings of the 2017 International Conference on Inventive Systems and Control (ICISC), Coimbatore, India. doi:10.1109/ICISC.2017.8068639
  • Patel, V. V. (2020). Ziegler-Nichols Tuning Method: Understanding the PID Controller. Resonance, 25(10), 1385-1397. doi:10.1007/s12045-020-1058-z
  • Pereira, D. S., & Pinto, J. O. P. (2005, July 24-28). Genetic Algorithm based system identification and PID tuning for optimum adaptive control. In: Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, CA, USA, (pp. 801-806). doi:10.1109/AIM.2005.1511081
  • Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal, 4(3), 409-421. doi:10.1016/J.ASEJ.2012.10.010
  • Saad, M. S., Jamaluddin, H., & Darus, I. Z. M. (2012). Implementation of PID controller tuning using differential evolution and genetic algorithms. International Journal of Innovative Computing Information and Control, 8(11), 7761-7779.
  • Tiwari, S., Bhatt, A., Unni, A. C., Singh, J. G., & Ongsakul, W. (2018, October 24-26). Control of DC Motor Using Genetic Algorithm Based PID Controller. In: Proceedings of the 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), Phuket, Thailand. doi:10.23919/ICUE-GESD.2018.8635662
  • Wati, D. A. R., & Hidayat, R. (2013, November 25-27). Genetic algorithm-based PID parameters optimization for air heater temperature control. In: Proceedings of the 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems (ROBIONETICS), Jogjakarta, Indonesia, (pp. 30-34). doi:10.1109/ROBIONETICS.2013.6743573
There are 21 citations in total.

Details

Primary Language English
Subjects Evolutionary Computation, Electrical Machines and Drives
Journal Section Electrical & Electronics Engineering
Authors

Zafer Ortatepe 0000-0001-7771-1677

Early Pub Date September 21, 2023
Publication Date September 29, 2023
Submission Date August 14, 2023
Published in Issue Year 2023

Cite

APA Ortatepe, Z. (2023). Genetic Algorithm based PID Tuning Software Design and Implementation for a DC Motor Control System. Gazi University Journal of Science Part A: Engineering and Innovation, 10(3), 286-300. https://doi.org/10.54287/gujsa.1342905